In a typical network-based merchandising environment, users can search for available items with several keywords related to the items. For example, a user may be able to search information about a specific item by providing a search engine with information such as a name of the item, a manufacturer name of the item, and/or characteristics of the item. However, as the size of the network-based merchandising environment has increased, so has the number of available items and information related to the available items. One aspect of this growth is that a typical search result is simply too large for the user to browse.
Oftentimes, the search results can be sorted so that the user is presented with the potentially most relevant item for which the user is searching. In the event that the search results are too large, users can submit additional search criteria or alternative search criteria in order to reduce the size of the search results. To enable users to easily accomplish this, some search engines provide additional search tools that facilitate the display of pre-categorization of the search results. The pre-categorization of the search results is provided to enable users to choose additional search criteria such as characteristics shared by numerous items or alternative search criteria of the search results.
Although the inclusion of pre-categorization can improve a general searching experience, users still can have difficulty utilizing pre-categorization to identify more relevant search criteria. In one aspect, the displayed pre-categorization, for example, search categories, typically does not reflect the particular attributes of the currently displayed search results. In some instances, the pre-categorization is displayed based on the cardinal number of corresponding data entries while the search results are displayed based on a degree of relevancy of data entries. This inconsistency between the displayed pre-categorization and the displayed search results can make a user confused when identifying more relevant search criteria from the displayed pre-categorization.
For example, if the search results are pre-categorized by a brand name, the most common brand names found in the data entries of the search results are typically displayed as top choices for pre-categorization. However, the most common brand names can be different from the brand names of the items which are determined to be potentially more relevant to the search query. For example, when a user is looking for a particular type of shoes but does not know that such type of shoes are typically manufactured under brand name “A,” the user may input a search query describing the particular type of shoes without specifying the brand name. Conventional search engines may determine items having the brand name “A” for more relevant items than items having other brand names and the search results are displayed accordingly. In some instances, the search result can be effectively narrowed down by the brand name “A.” However, the brand name “A” may not be presented as the first choice of the pre-categorization unless the brand name “A” is determined to be the most common brand name. Such deficiency can lead the user to choose the less relevant brand names over the brand name “A,” which tend to result in a search of less relevant items.